A fresh viewpoint on drug discovery, pharma, and biotech

About BiopharmaTrend.com

Digital revolution happened in 1950-1970 and it changed the way people live and communicate forever.
The healthcare industry is not an exception and it has been largely transformed by the emergence of new software tools,
communication and collaboration platforms, process automation tools, data analytics technologies and sophisticated database management and IT infrastructure models.

But healthcare industry is on the verge of a new digital transformation again -- this time it relates to big data analytics, cloud technologies, and machine learning.
Accompanied by a skyrocketing progress in biological sciences — genomics, cell technologies, gene editing, new biologics drugs,
as well as unprecedented access to a huge drug-like chemical space (hundreds of millions of compounds, and even billions — with DNA-encoded libraries, for example)
— we are about to create the future where things like Precision Medicine can become possible on a global scale.

Imagine that people could get personalized drugs or therapy treatments, which are specifically designed for each particular patient, taking into account their genetics,
medical history, and an overall lifestyle. Diminished side effects, high efficiency — access to healthy living.

At this blog, we are reviewing hi-tech and data technologies and innovations, emerging informatics startups and growing industry trends shaping drug discovery and biopharmaceutical industry.
We are providing insightful opinions on new hi-tech products, services, and use cases.

Some of the topics at this website include:

Machine Learning and Artificial Intelligence in drug discovery and healthcare

Disclaimer:

We are doing our best to check all the facts we are mentioning in our papers and substantiate conclusions and trends by relevant and reliable data.
However, all the materials and suggestions in this website are of consulting nature only and we bear no responsibility for their use by our readers.
We shall bear no liability whatsoever for any losses, wrong decisions or damages incurred by our readers and their companies as a result of reading and interpreting
our articles and conclusions. In all cases, it is your responsibility to check data and confirm conclusions by your own means before making any business or otherwise
important decisions and actions.